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In this paper, a global optimization technique is applied to solve the optimal transmitter placement problem for indoor wireless systems. An efficient pattern search algorithm-DIRECT (DIviding RECTangles) of Jones, Perttunen, and Stuckman (1993)-has been connected to a parallel 3D radio propagation ray tracing modeler running on a 200node Beowulf cluster of Linux workstations. Surrogate functions for a parallel WCDMA (wideband code division multiple access) simulator were used to estimate the system performance for the global optimization algorithm. Power coverage and BER (bit error rate) are considered as two different criteria for optimizing locations of a specified number of transmitters across the feasible region of the design space. This paper briefly describes the underlying radio propagation and WCDMA simulations and focuses on the design issues of the optimization loop.

Abstract. This paper describes several massively parallel implementations for a global search algorithm DIRECT. Two parallel schemes take different approaches to address DIRECT's design challenges imposed by memory requirements and data dependency. Three design aspects in topology, data structures, and task allocation are compared in detail. The goal is to analytically investigate the strengths and weaknesses of these parallel schemes, identify several key sources of inefficiency, and experimentally evaluate a number of improvements in the latest parallel DIRECT implementation. The performance studies demonstrate improved data structure efficiency and load balancing on a 2200 processor cluster.

In this paper, we examine the evolution of the impact of older scholarly articles. We attempt to answer four questions. First, how often are older articles cited in scholarly papers and how has this changed over time. Second, how does the impact of older articles vary across different fields of scholarship. Third, is the change in the impact of older articles accelerating or slowing down. Fourth, are these trends different for much older articles.To answer these questions, we studied citations from articles published in 1990-2013. We computed the fraction of citations to older articles from articles published each year as the measure of impact for the study. For this study, we considered articles that were published at least 10 years before the citing article as older articles. To explore how changes in citation behavior differ across areas of research, we computed these numbers for 261 subject categories and 9 broad areas of research. Finally, we repeated the computation for two other definitions of older articles, 15 years and older and 20 years and older.There are three major conclusions from our study. First, the impact of older articles has grown substantially over 1990-2013. Our analysis indicates that, in 2013, 36% of citations were to articles that are at least 10 years old and that this fraction has grown 28% since 1990. The fraction of older citations increased over 1990-2013 for 7 out of 9 broad areas of research and 231 out of 261 subject categories.Second, the change over the second half (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) was significantly larger than that over first half (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001) -the increase in the second half was double the increase in the first half.Third, the trend of a growing impact of older articles also holds for articles that are at least 15 years old and those that are at least 20 years old. In 2013, 21% of citations were to articles ≥ 15 years old with an increase of 30% since 1990 and 13% of citations were to articles ≥ 20 years old with an increase of 36% over the same period. Now that finding and reading relevant older articles is about as easy as finding and reading recently published articles, significant advances aren't getting lost on the shelves and are influencing work worldwide for years after.

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Modeling and analysis techniques are used to investigate the performance of a massively parallel version of DIRECT, a global search algorithm widely used in multidisciplinary design optimization applications. Several high-dimensional benchmark functions and real world problems are used to test the design effectiveness under various problem structures. In this second part of a two-part work, theoretical and experimental results are compared for two parallel clusters with different system scale and network connectivity. The first part studied performance sensitivity to important parameters for problem configurations and parallel schemes, using performance metrics such as memory usage, load balancing, and parallel efficiency. Here linear regression models are used to characterize two major overhead sources-interprocessor communication and processor idleness-and also applied to the isoefficiency functions in scalability analysis. For a variety of high-dimensional problems and large scale systems, the massively parallel design has achieved reasonable performance. The results of the performance study provide guidance for efficient problem and scheme configuration. More importantly, the design considerations and analysis techniques generalize to the transformation of other global search algorithms into effective large scale parallel optimization tools.

Modeling and analysis techniques are used to investigate the performance of a massively parallel version of DIRECT, a global search algorithm widely used in multidisciplinary design optimization applications. Several high-dimensional benchmark functions and real world problems are used to test the design effectiveness under various problem structures. Theoretical and experimental results are compared for two parallel clusters with different system scale and network connectivity. The present work aims at studying the performance sensitivity to important parameters for problem configurations, parallel schemes, and system settings.The performance metrics include the memory usage, load balancing, parallel efficiency, and scalability. An analytical bounding model is constructed to measure the load balancing performance under different schemes. Additionally, linear regression models are used to characterize two major overhead sources-interprocessor communication and processor idleness, and also applied to the isoefficiency functions in scalability analysis. For a variety of high-dimensional problems and large scale systems, the massively parallel design has achieved reasonable performance. The results of the performance study provide guidance for efficient problem and scheme configuration. More importantly, the generalized design considerations and analysis techniques are beneficial for transforming many global search algorithms to become effective large scale parallel optimization tools.